1. Field of the Invention
The present invention relates to a method of compressing a digital audio signal with high efficiency prior to transmission.
2. Description of the Prior Art
To compress an audio signal, it is customary to divide the input audio signal into a plurality of channels in time domain or in the frequency domain and adaptively allocate a number of bits to the divided audio signal in each of the channels. In one process, known as subband coding (SBC), the audio signal in the time domain is compressed by dividing it into a plurality of frequency bands among which bit allocation is performed. In adaptive transform coding (ATC), an audio signal in the time domain is converted into a signal in the frequency domain by an orthogonal transform, the resulting spectral coefficients in the frequency domain are divided into a plurality of frequency bands, and the spectral coefficients in each of the frequency bands are adaptively quantized. In yet another process, known as adaptive bit allocation (APC-AB), subband coding (SBC) and adaptive predictive coding (APC) are combined to divide a signal in the time domain into a plurality of frequency bands, and each frequency band signal is converted into a base band (low frequency band), after which linear predictive analyses of plural orders are carried out for predictive coding.
Among the above-mentioned high efficiency compression processes, in adaptive transform coding, an audio signal in the time domain is converted into spectral coefficients in the frequency domain, orthogonal to the time domain, using an orthogonal transform, such as a fast Fourier transform (FFT) or a discrete cosine transform (DCT). The spectral coefficients are then divided into a plurality of frequency bands, and the spectral coefficients in each of the frequency bands are quantized by adaptive bit allocation. One example of the quantizing in adaptive transform coding using a fast Fourier transform is as follows: as shown in FIG. 1 of the accompanying drawings, the spectral amplitudes Am, resulting from subjecting the digital audio signal to the fast Fourier transform, are divided into bands B1, B2, . . . , and the additional information which is required to quantize the amplitudes of the spectral coefficients in each of the bands is calculated. Thereafter, using the calculated additional information, the amplitudes in each of the bands are quantized, and the additional information is also quantized.
With the above the high efficiency compression process in which an audio signal in the time domain is converted into coefficients in a domain orthogonal to the time domain using an orthogonal transform, it is the general practice to determine a masking threshold from the power in each band, and to effect dynamic bit allocation in the frequency domain in a manner that reduces quantizing noise to a level below the level of a masking threshold. The width of each band is determined by the characteristics of the human sense of hearing, i.e., the ability of human beings to perceive sound. By processing the spectral coefficients in each band in the manner described above, the audio signal from which the spectral coefficients are derived is compressed with high efficiency by exploiting the simultaneous masking characteristic of the human sense of hearing.
However, conventional compression processes have not fully exploited the characteristics, such as the masking effect, of the human sense of hearing.